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Late Cretaceous Deformation of the Arabian Plate: Analogue Modelling and Geodynamic Implications
No full textThe Late Cretaceous deformation phase of the Arabian Plate remains poorly understood, despite its critical role in forming structural traps within some of the world’s largest petroleum systems, such as the Ghawar Field ( Afifi, 2005 ). To better constrain the tectonic activity during this period, a comprehensive literature review was conducted to identify the main active structural features across the Arabian Plate. These structures were then incorporated into a series of analogue sandbox experiments designed to test how the orientation of pre-existing weaknesses influences fault patterns under strike-slip and oblique convergence settings. This ongoing research aims to refine our understanding of the tectonic regimes that prevailed during the Late Cretaceous and to advance our knowledge of the Arabian Peninsula’s petroleum systems. Ultimately, this study may lead to the development of a simplified plate-tectonic model that explains the coexistence of NW–SE-trending transtensional structures in the northern Arabian Plate and NNW–SSE-trending transpressional structures in the south
The Coral Holobiont
No full textHere we emphasize the crucial role of microbial communities in the biology of coral hosts, presenting the concept of the coral holobiont as the main unit interacting with other organisms and the environment. This concept offers profound insights into the symbiotic relationships that define coral health and resilience, guiding future research and conservation efforts.EOO and ES were funded by postdoctoral fellowships provided by Ocean Science and Solutions Applied Research Institute (OSSARI), Education, Research, and Innovation (ERI) Sector, NEOM, Tabuk, Saudi Arabia
RIS-Aided Protected Zone Formation for Physical Layer Security of In-Band Full Duplex Systems
No full textThe rapid evolution of mobile technologies presents a formidable security challenge, as traditional cryptographic methods struggle to keep pace. Integrating physical layer security (PLS) solutions with cutting-edge technologies such as in-band full-duplex (IBFD) and reconfigurable intelligent surfaces (RISs) holds promise for addressing these challenges effectively. This study introduces a novel RIS-driven protected zone (PZ) formation approach that employs artificial noise (AN) to safeguard legitimate users without requiring a priori knowledge of eavesdropper locations, channels, or numbers. The proposed methodology partitions the RIS into two distinct segments: while the former segment enhances the achievable data rate for legitimate signal, the latter segment concurrently amplifies AN to jam illegitimate users within the PZ.We present formulations and solutions for maximizing secrecy capacity (SC) and minimizing power consumption through optimized transmit power allocation factors, RIS segmentation, and beams’ directions, all subject to stringent quality-of-service (QoS) constraints. Closed-form expressions are derived to facilitate efficient implementation and performance optimization. Simulation results validate closed-form solutions and demonstrate that the proposed scheme can significantly enhance SC compared to benchmarks where RIS and AN are used separately, with the proposed scheme achieving approximately 81% greater capacity than the “RIS-Only” approach and a substantial advantage over the “AN-Only” approach, which results in no secrecy. Additionally, this work includes an analysis of energy efficiency, emphasizing the critical importance of optimizing power consumption in practical applications. This dual focus on improving security while effectively managing energy resources underscores the scheme’s practical relevance and efficiency.We acknowledge that extending the proposed approach to more practical scenarios would require substantial modifications to the design methodolog
LYCOPENE β-CYCLASE overexpression improves growth, modulates hormone content, and affects rhizospheric interactions in tobacco and tomato roots
No full textKey messageExpression of plant LYCOPENE β-CYCLASEs modulates abscisic acid and strigolactone contents resulting in enhanced root length, impaired mycorrhiza colonization frequency, and reduced Striga-seed germination in tobacco and tomato. Genetic engineering of the carotenoid biosynthesis made possible the biofortification of many crops by enhancing the provitamin A content in their edible parts. Recent studies showed that overexpression of a single carotenogenic gene, the LYCOPENE β-CYCLASE (LCYB), impacted plant architecture, and improved photosynthesis efficiency and stress tolerance in tobacco (Nicotiana tabacum cv. Xanthi) and tomato (Solanum lycopersicum). Here, we show that LCYB overexpression also enhanced root growth and biomass, and affected rhizospheric interactions, causing a reduction in mycorrhization and decreased capability to induce seed germination in root parasitic plants. These below-ground effects in tobacco and tomato are associated with changes in the levels of carotenoids, apocarotenoids, and phytohormones. Our findings highlight LCYB as a key regulatory and metabolic hotspot in the carotenoid pathway. Its overexpression induces profound changes in root architecture and below-ground interactions. These results lay the foundation for a new generation of crops that can better face the future environmental stress caused by global warming and show increased resistance to root parasitic plants.The authors thank Dr. Ralph Bock for providing the transplastomic pNLYC#2 and pNLYC#22 seeds. The authors are grateful to Saad Hammad and Vijayalakshmi Ponnakanti for greenhouse support. Research reported in this publication was supported by baseline funding given to Salim Al-Babili from King Abdullah University of Science and Technology (KAUST).
Open access publishing provided by King Abdullah University of Science and Technology (KAUST). The work of Salim Al-Babili was funded by King Abdullah University of Science and Technology, Baseline
Enhancing Wireless Backhaul Networks With Parallel FSO-mmWave Systems: Experimental Analysis and Availability Assessment
No full textIn this work, we report the deployment and experimental analysis of a hybrid free-space optical (FSO) and millimeter-wave (mmWave) backhaul system over a 1.2 km link to connect an underserved area. The parallel configuration of FSO and mmWave enables mutual backup during adverse weather, improving service availability to 99.10%, compared to 81.90% and 90.99% for standalone FSO and mmWave, respectively. Empirical measurements, supported by Monte Carlo simulations, confirm strong agreement with theoretical log-normal (FSO) and Gaussian (mmWave) models. Environmental analysis revealed that wind speed induces misalignment and power loss in FSO, while humidity significantly degrades mmWave performance but has minimal impact on FSO at 1550 nm. These complementary behaviors highlight the practicality of hybrid deployment, offering a cost-effective and resilient alternative to fiber for bridging the digital divide and ensuring high-speed connectivity in challenging environments.The authors would like to thank Dr. Abderrahmen Trichili for technical comments and suggestions
CCDC 2426059: Experimental Crystal Structure Determination :
No full textAn entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures
Hybrid Physics–Data Driven Reduced Modeling for Reservoir Simulation
No full textReservoir simulation is crucial for optimizing geo-energy and geo-storage systems. Despite advances in numerical techniques and high-performance computing (HPC), realistic reservoir models remain computationally prohibitive for tasks like assisted history matching, uncertainty quantification, and optimization, which require numerous forward simulation runs. This necessitates using surrogate models that approximate reference model outputs with reduced computational loads.
Hybrid methods, such as numerical graph network models, have gained interest due to their ease of implementation and superior predictive capability compared to fully data-driven models. These models combine mathematical modeling of flow physics on coarse or reduced grids, which can be calibrated to match reference simulation outputs or well observation data.
The coarse grid network (CGNet) differs from other hybrid methods for using finite volume methods (FVM) represented as a graph made from coarse partition of the original reference model grid. This approach provides more connections and tunable parameters, making CGNet flexible and physically interpretable. However, CGNet's application for complex flow physics, such as fractured reservoirs, and optimization in large-scale models with hundreds of wells and multilayered reservoirs, remains underexplored. These gaps present significant research opportunities.
The initial phase of this research extended CGNet's capabilities to handle a broader range of flow physics and applications. Notably, CGNet was adapted for rate management, incorporating plume distribution data to enhance predictive capability. This is vital for carbon capture and storage (CCS), where accurate plume prediction ensures effective storage and monitoring.
The next phase will develop additional fracture model representations, targeting dual-continuum models for implicit small-scale fracture representation. This broadens CGNet's applicability to reservoirs with multiscale fracture networks. Another key aspect is integrating CGNet with a multifidelity optimization framework, leveraging both high-fidelity and low-fidelity models to balance computational efficiency and accuracy, reducing the need for frequent recalibration.
The research will also apply these enhanced models in more realistic reservoir settings to demonstrate CGNet's practical applicability in real-world operations. The ultimate goal is to develop an integrated framework that combines graph network surrogate models with multifidelity optimization techniques. This framework aims to provide an efficient tool for forecasting reservoir performance and guiding management decisions, such as optimizing well rate control
Stabilizing Zinc Anodes with Water-Soluble Polymers as an Electrolyte Additive
No full textWater-induced corrosion and zinc dendrite formation seriously disrupt the Zn plating/stripping process at the anode/electrolyte interface, which results in the instability of the Zn metal anode in aqueous zinc-ion batteries. To address the issues of the zinc metal anode, three water-soluble polymers with different hydrophilic groups—polyacrylic acid (PAA), polyacrylamide (PAM), and polyethylene glycol (PEG)—were designed as electrolyte additives in ZnSO4 electrolytes. Among them, the PAA-based system exhibited an optimal electrochemical performance, achieving a stable cycling for more than 360 h at a current density of 5 mA cm−2 with an areal capacity of 2 mA h cm−2. This improvement could be attributed to its carboxyl groups, which effectively suppresses zinc dendrite growth, electrode corrosion, and side reactions, thereby enhancing the cycling performance of zinc-ion batteries. This work provides a reference for the optimization of zinc anodes in aqueous zinc-ion batteries.This research was funded by the financial support of National Natural Science Foundation of China (22102157), Fundamental Research Program of Shanxi Province (202303021212214), Reward Program for Excellent Doctoral Graduates to Work in Shanxi (20222095), and Taiyuan University of Science and Technology Scientific Research Initial Funding (20222027)
Supplementary material 3. Family abundance profiles of Hatiba Mons coassemblies and assemblies sediments and mats samples
No full textFamily abundance profiles of coassemblies and assemblies of Hatiba Mons hydrothermal vents' sediment and mat samples. Supplementary material 3 is part of the MSc Thesis of Paula Garcia Martinez
A Robust Auto-Encoder HBC Transceiver with CGAN-Based Channel Modeling
No full textHuman body communication (HBC) offers a promising alternative for efficient and secure data transmission in wearable healthcare systems by leveraging the body’s conductive properties. By utilizing the conductive properties of the human body, HBC offers significant advantages over conventional radio frequency wireless communication methods, including ultra-low power consumption and minimal interference. However, HBC systems face key challenges in energy efficiency, data rate optimization, channel adaptability, and accurate body channel modeling. In this paper, we present a novel dual-mode HBC transceiver architecture designed to overcome these challenges by integrating autoencoder-based signal processing with Generative adversarial networks (GANs)-driven channel modeling framework to enhance communication reliability. Operating in both broadband and narrowband modes, the transceiver dynamically adjusts its data rate and power efficiency based on application-specific demands. The design process involves first developing a CGAN-based channel model from real HBC measurements, then using this model to train an autoencoder-based transceiver architecture. Our CGAN framework generates realistic synthetic channel responses for training, enabling the autoencoder to learn optimal encoding and decoding strategies that are robust to channel variations. Subsequently, we developed a low-power hardware architecture that supports flexible data rates of the proposed design while ensuring robust performance in diverse scenarios. This systematic approach provides key advantages: improved channel modeling accuracy achieving a 0.9 correlation coefficient between generated and real channels and mean squared error of 0.0071, reduced hardware complexity through elimination of DAC/ADC, and flexible operation with dual-mode support. Operating at a clock speed of 42 MHz in the narrowband mode, the transceiver achieves an energy efficiency of 349 pJ/bit at a data rate of 262.5 kbps with sensitivity of -64 dBm, appealing for long-range and low-power applications. In broadband mode, the transceiver achieves an energy efficiency of 16 pJ/bit at a data rate of 5.25 Mbps, suitable for applications demanding high data rates over shorter distances. (Figure presented